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Industry 4.0 imposes many challenges for manufacturing companies and their employees. Innovative and effective training strategies are required to cope with fast-changing production environments and new manufacturing technologies. Virtual Reality (VR) offers new ways of on-the-job, on-demand, and off-premise training. A novel concept and evaluation system combining Gamification and VR practice for flexible assembly tasks is proposed in this paper and compared to existing works. It is based on directed acyclic graphs and a leveling system. The concept enables a learning speed which is adjustable to the users’ pace and dynamics, while the evaluation system facilitates adaptive work sequences and allows employee-specific task fulfillment. The concept was implemented and analyzed in the Industry 4.0 model factory at FH Aachen for mechanical assembly jobs.
Control engineering theory is hard to grasp for undergraduates during the first semesters, as it deals with the dynamical behavior of systems also in combination with control strategies on an abstract level. Therefore, operational amplifier (OpAmp) processes are reasonable and very effective systems to connect mathematical description with actual system’s behavior. In this paper, we present an experiment for a laboratory session in which an embedded system, driven by a LabVIEW human machine interface (HMI) via USB, controls the analog circuits.With this setup we want to show the possibility of firstly, analyzing a first order process and secondly, designing a P-and PI-controller. Thereby, the theory of control engineering is always applied to the empirical results in order to break down the abstract level for the students.
A further development of the Added-Mass-Method allows the combined representation of the effects of both soil-structure-interaction and fluid-structure interaction on a liquid-filled-tank in one model. This results in a practical method for describing the dynamic fluid pressure on the tank shell during joint movement. The fluid pressure is calculated on the basis of the tank's eigenform and the earthquake acceleration and represented by additional masses on the shell. The bearing on compliant ground is represented by replacement springs, which are calculated dependent on the local soil composition. The influence of the shear modulus of the compliant soil is clearly visible in the pressure curves and the stress distribution in the shell. The acceleration spectra are also dependent on soil stiffness. According to Eurocode-8 the acceleration spectra are determined for fixed soil-classes, instead of calculating the accelerations for each site in direct dependence on the soil composition. This leads to unrealistic sudden changes in the system's response. Therefore, earthquake spectra are calculated for different soil models in direct dependence of the shear modulus. Thus, both the acceleration spectra and the replacement springs match the soil composition. This enables a reasonable and consistent calculation of the system response for the actual conditions at each site.
Reinforced concrete (RC) structures with masonry infills are widely used for several types of buildings all over the world. However, it is well known that traditional masonry infills constructed with rigid contact to the surrounding RC frame performed rather poor in past earthquakes. Masonry infills showed severe in-plane damages and failed in many cases under out-of-plane seismic loading. As the undesired interactions between frames and infills changes the load transfer on building level, complete collapses of buildings were observed. A possible solution is uncoupling of masonry infills to the frame to reduce the infill contribution activated by the frame deformation under horizontal loading. The paper presents numerical simulations on RC frames equipped with the innovative decoupling system INODIS. The system was developed within the European project INSYSME and allows an effective uncoupling of frame and infill. The simulations are carried out with a micro-modelling approach, which is able to predict the complex nonlinear behaviour resulting from the different materials and their interaction. Each brick is modelled individually and connected taking into account nonlinearity of a brick mortar interface. The calibration of the model is based on small specimen tests and experimental results for one bay one storey frame are used for the validation. The validated model is further used for parametric studies on two storey and two bay infilled frames. The response and change of the structural stiffness are analysed and compared to the traditionally infilled frame. The results confirm the effectiveness of the INODIS system with less damage and relatively low contribution of the infill at high drift levels. In contrast to the uncoupled system configurations, traditionally infilled frames experienced brittle failure at rather low drift levels.
The implementation of IO-Link in the automation industry has increased over the years. Its main advantage is it offers a digital point-to-point plugand-play interface for any type of device or application. This simplifies the communication between devices and increases productivity with its different features like self-parametrization and maintenance. However, its complete potential is not always used.
The aim of this paper is to create an Arduino based framework for the development of generic IO-Link devices and increase its implementation for rapid prototyping. By generating the IO device description file (IODD) from a graphical user interface, and further customizable options for the device application, the end-user can intuitively develop generic IO-Link devices. The peculiarity of this framework relies on its simplicity and abstraction which allows to implement any sensor functionality and virtually connect any type of device to an IO-Link master. This work consists of the general overview of the framework, the technical background of its development and a proof of concept which demonstrates the workflow for its implementation.
The production of dispatchable renewable energy will be one of the most important key factors of the future energy supply. Concentrated solar power (CSP) plants operated with molten salt as heat transfer and storage media are one opportunity to meet this challenge. Due to the high concentration factor of the solar tower technology the maximum process temperature can be further increased which ultimately decreases the levelized costs of electricity of the technology (LCOE). The development of an improved tubular molten salt receiver for the next generation of molten salt solar tower plants is the aim of this work. The receiver is designed for a receiver outlet temperature up to 600 °C. Together with a complete molten salt system, the receiver will be integrated into the Multi-Focus-Tower (MFT) in Jülich (Germany). The paper describes the basic engineering of the receiver, the molten salt tower system and a laboratory corrosion setup.
The paper presents a method for the quantitative assessment of choroidal blood flow using an OCT-A system. The developed technique for processing of OCT-A scans is divided into two stages. At the first stage, the identification of the boundaries in the selected portion was performed. At the second stage, each pixel mark on the selected layer was represented as a volume unit, a voxel, which characterizes the region of moving blood. Three geometric shapes were considered to represent the voxel. On the example of one OCT-A scan, this work presents a quantitative assessment of the blood flow index. A possible modification of two-stage algorithm based on voxel scan processing is presented.
In collaborative research projects, both researchers and practitioners work together solving business-critical challenges. These projects often deal with ETL processes, in which humans extract information from non-machine-readable documents by hand. AI-based machine learning models can help to solve this problem.
Since machine learning approaches are not deterministic, their quality of output may decrease over time. This fact leads to an overall quality loss of the application which embeds machine learning models. Hence, the software qualities in development and production may differ.
Machine learning models are black boxes. That makes practitioners skeptical and increases the inhibition threshold for early productive use of research prototypes. Continuous monitoring of software quality in production offers an early response capability on quality loss and encourages the use of machine learning approaches. Furthermore, experts have to ensure that they integrate possible new inputs into the model training as quickly as possible.
In this paper, we introduce an architecture pattern with a reference implementation that extends the concept of Metrics Driven Research Collaboration with an automated software quality monitoring in productive use and a possibility to auto-generate new test data coming from processed documents in production.
Through automated monitoring of the software quality and auto-generated test data, this approach ensures that the software quality meets and keeps requested thresholds in productive use, even during further continuous deployment and changing input data.